ESKAPE Act Plus: Pathway Activation Analysis for Bacterial Pathogens

ABSTRACT The last 20 years have witnessed an explosion in publicly available gene expression and proteomic data and new tools to help researchers analyze these data. Tools typically include statistical approaches to identify differential expression, integrate prior knowledge, visualize results, and suggest how differential expression relates to changes in phenotype. Here, we provide a simple web-based tool that bridges some of the gaps between the functionality available to those studying eukaryotes and those studying prokaryotes. Specifically, our Shiny web application ESKAPE Act PLUS allows researchers to upload results of high-throughput bacterial gene or protein expression experiments from 13 species, including the six ESKAPE pathogens, to our system and receive (i) an analysis of which KEGG pathways or GO terms are significantly activated or repressed, (ii) visual representations of the magnitude of activation or repression in each category, and (iii) detailed diagrams showing known relationships between genes in each regulated KEGG pathway and fold changes of individual genes. Importantly, our statistical approach does not require users to identify which genes or proteins are differentially expressed. ESKAPE Act PLUS provides high-quality statistics and graphical representations not available using other web-based systems to assess whether prokaryotic biological functions are activated or repressed by experimental conditions. To our knowledge, ESKAPE Act PLUS is the first application that provides pathway activation analysis and pathway-level visualization of gene or protein expression for prokaryotes. IMPORTANCE ESKAPE pathogens are bacteria of concern because they develop antibiotic resistance and can cause life-threatening infections, particularly in more susceptible immunocompromised people. ESKAPE Act PLUS is a user-friendly web application that will advance research on ESKAPE and other pathogens commonly studied by the biomedical community by allowing scientists to infer biological phenotypes from the results from high-throughput bacterial gene or protein expression experiments. ESKAPE Act PLUS currently supports analysis of 23 strains of bacteria from 13 species and can also be used to re-analyze publicly available data to generate new findings and hypotheses for follow-up experiments.


Reviewer #1 (Comments for the Author):
Overall, this is a very well written manuscript. In addition, the website for ESKAPE ACT Plus, the sample data set provided, and the user manual that can be found on the website were all helpful. I was successfully able to use the sample data set to evaluate the functionality of the web tool and found the overall experience to be clear and easy to use. I do have one suggestion, although this may not be be possible for technical reasons of the website. I do like the figures that can be generated using the webtool, but the image quality is not high quality enough that it would be appropriate for publication. Is it possible to include an option for downloading a higher resolution PNG image or a vector file?
Reviewer #3 (Comments for the Author): The integration of technology and computer science in the scientific community is very necessary and exhibits an important factor in the advancement of the field. The developed web application is an excellent example of the integration of such. The simplicity of the representation and model is very crucial, particularly to the bacterial pathogens which are very prone to AMR. The public issue of AMR is a global problem which requires attention and subsequent approaches to combat AMR.

Reviewer #5 (Comments for the Author):
This work by Koeppen et al aims at providing the microbial scientific community with an easy-to-use tool to perform pathway activation analysis (and visualization) using omics expression data. While the tool is already available online at no cost, this short report i) documents the methodology, function, and output of ESKAPE Act PLUS, ii) provides a proof of concept/superiority by re-analyzing a publicly available dataset and, iii) briefly compares strengths and weaknesses to existing tools. The manuscript is clearly written (as is the user manual available on the webpage) and such tools are clearly needed but, in this reviewer's opinion, a number of limitations exist and might limit the impact and future use. This is further detailed in the specific remarks below. Major remarks: 1. While likely accurate, the statement that the species/strains for which ESKAPE Act PLUS is available are "the most commonly used strains in biomedical high-throughput experiments" is not substantiated by reference 9 or by quantitative data. More importantly, in the genomic era, the availability of only 23 strains might be an important limitation for the wide use of this tool by the community. At the time of this review, pathways for >7,000 bacterial strains are available in the KEGG database. What limits the integration of those into ESKAPE Act PLUS? are there plans to expand to more strains/species in the future? 2. The description of ESKAPE Act PLUS is well detailed in the "features and capabilities" section of the main text but it is somehow underwhelming in the figures and visuals. This is particularly notable as ESKAPE Act PLUS is offered as a visualization tool. As an example, the pathway level visualization/graphs (which is a clear, defining feature of ESKAPE Act PLUS) is only displayed as a small snapshot, low-resolution snapshot on Figure 1 and details are not readable. 3. Expending on point #2, the proof-of-concept using the Enterococcus dataset is interesting but might not have been the best choice to display the power of ESKAPE Act PLUS. A genome-wide dataset (similar to the one available for PA14 on the website) with notable differences observable on pathways/maps would better illustrate the strengths of the tools and attract the attention of future users. 4. The comparison to existing tools is a key aspect of this publication. While capabilities are summarized in table 1, the performance of the tools are not compared and contrasted using a common dataset which, in this reviewer's opinion, limits the ability of a reader to make an informed decision. Finally, other tools like DAVID and ProkSeq have either been widely used (DAVID) or provide a complete analytical pipeline from the fastq reads to pathways visuals (ProkSeq) and should likely be discussed in this manuscript.
Minor remarks: 1. Please add line numbering to the draft manuscript to facilitate referencing during the review process. 2. Page 3, line 3 of introduction. Revise "medial" to "medical" 3. Page 3, line 10 of introduction. Should this read "species" instead of strains. Or maybe XX strains from YY species.

Title: ESKAPE Act Plus: Pathway Activation Analysis for Bacterial Pathogens
Comments: The integration of technology and computer science in the scientific community is very necessary and exhibits as an important factor in the advancement of the field. The developed web application is an excellent example of the integration of such. The simplicity of the representation and model is very crucial particularly to the pathogens which are very prone to AMR. The public issue of AMR is a global problem which requires attention and subsequent approaches to combat AMR. Overall, this is a very well written manuscript. In addition, the website for ESKAPE ACT Plus, the sample data set provided, and the user manual that can be found on the website were all helpful. I was successfully able to use the sample data set to evaluate the functionality of the web tool and found the overall experience to be clear and easy to use. I do have one suggestion, although this may not be be possible for technical reasons of the website. I do like the figures that can be generated using the webtool, but the image quality is not high quality enough that it would be appropriate for publication. Is it possible to include an option for downloading a higher resolution PNG image or a vector file?
Response: The overview graphs for significantly activated or repressed KEGG pathways or GO terms are high resolution publication quality pdf files. The individual KEGG pathway images are png files, but unfortunately, their resolution is limited by the original source KEGG graphs, which are raster images.

Reviewer #3 (Comments for the Author):
The integration of technology and computer science in the scientific community is very necessary and exhibits an important factor in the advancement of the field. The developed web application is an excellent example of the integration of such. The simplicity of the representation and model is very crucial, particularly to the bacterial pathogens which are very prone to AMR. The public issue of AMR is a global problem which requires attention and subsequent approaches to combat AMR.

Reviewer #5 (Comments for the Author):
This work by Koeppen et al aims at providing the microbial scientific community with an easy-to-use tool to perform pathway activation analysis (and visualization) using omics expression data. While the tool is already available online at no cost, this short report i) documents the methodology, function, and output of ESKAPE Act PLUS, ii) provides a proof of concept/superiority by re-analyzing a publicly available dataset and, iii) briefly compares strengths and weaknesses to existing tools. The manuscript is clearly written (as is the user manual available on the webpage) and such tools are clearly needed but, in this reviewer's opinion, a number of limitations exist and might limit the impact and future use. This is further detailed in the specific remarks below.
Major remarks: 1. While likely accurate, the statement that the species/strains for which ESKAPE Act PLUS is available are "the most commonly used strains in biomedical high-throughput experiments" is not substantiated by reference 9 or by quantitative data. More importantly, in the genomic era, the availability of only 23 strains might be an important limitation for the wide use of this tool by the community. At the time of this review, pathways for >7,000 bacterial strains are available in the KEGG database. What limits the integration of those into ESKAPE Act PLUS? are there plans to expand to more strains/species in the future?

Response: The strains currently supported by ESKAPE Act PLUS are based on those strains that are most frequently used in research experiments as determined by transcriptomics data deposited in Sequence Read Archive (SRA) as well as proteomics data deposited in the PRoteomics IDEntifications Database (PRIDE). A statement explaining the strain selection can be found on lines 136-138 of the manuscript.
A major limitation to the number of supported strains is that ensuring correct annotation and proper functionality is a manual process that does not scale to hundreds or thousands of strains. We are planning to add additional strains in the future upon user request.
2. The description of ESKAPE Act PLUS is well detailed in the "features and capabilities" section of the main text but it is somehow underwhelming in the figures and visuals. This is particularly notable as ESKAPE Act PLUS is offered as a visualization tool. As an example, the pathway level visualization/graphs (which is a clear, defining feature of ESKAPE Act PLUS) is only displayed as a small snapshot, low-resolution snapshot on Figure 1 and details are not readable. Figure 1 is to provide an overview of the application and its outputs. Figure 2 includes larger, high-resolution images of summary graphs for significant KEGG pathways and GO terms and in the new version of the manuscript, we have included a second case study (lines 220-234) and a new figure (Fig. 3) that showcases the pathway level output. Due to copyright restrictions, we cannot use pathview output images in a publication. Therefore, we have updated ESKAPE Act PLUS to use KEGG Mapper instead of pathview to generate improved pathway level images and we have received permission to use the resulting images in our publication. KEGG Mapper has the additional benefit of providing a more user-friendly experience and much shorter processing time compared to pathview. In the new version of the manuscript, we have replaced the methods section about pathview with a description of and references to KEGG Mapper (lines 301-310). Your manuscript has been accepted, and I am forwarding it to the ASM Journals Department for publication. For your reference, ASM Journals' address is given below. Before it can be scheduled for publication, your manuscript will be checked by the mSystems production staff to make sure that all elements meet the technical requirements for publication. They will contact you if anything needs to be revised before copyediting and production can begin. Otherwise, you will be notified when your proofs are ready to be viewed.

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